Insolvency in Brazilian Football Clubs: Proposition of Models Based on Neural Networks

ABSTRACT The literature underlines that football clubs face financial problems, which can lead to insolvency. Existing models seek to predict insolvency for organizations in different sectors, but only recently have they been developed for European clubs. Thus, this study proposes insolvency prediction models for Brazilian football clubs. Based on the ranking elaborated by the Brazilian Football Confederation, we analyzed 35 football clubs that published their complete financial statements from 2011 to 2018. Financial and sports indicators were considered in the development of our neural network-based models. Results indicated that the variables immediate liquidity, net working capital, asset turnover, and sports performance in the Brazilian Championship were significant for predicting insolvency in at least one of the developed models. This study contributes to the literature on football clubs’ insolvency by proposing accurate predictive models based on financial and sporting indicators.